Apparatus and method for analyzing cross-enterprise radio frequency tag information

ABSTRACT

The invention includes a computer readable medium with executable instructions to analyze radio frequency (RF) tag information. The executable instructions access cross-enterprise RF tag information, identify a product transition based upon the cross-enterprise RF tag information, define a new product path based upon the product transition, and apply logic to the new product path to facilitate cross-enterprise product flow analysis.

CROSS REFERENCE TO RELATED APPLICATIONS

This application claims the benefit of U.S. Provisional PatentApplication No. 60/639,019, entitled, “Apparatus and Method forAnalyzing Cross-Enterprise Radio Frequency Tag Information,” filed Dec.23, 2004, the contents of which are hereby incorporated by reference intheir entirety.

BRIEF DESCRIPTION OF THE INVENTION

This invention relates generally to radio frequency tags that are usedto uniquely identify products. More particularly, this invention relatesto analyzing radio frequency tag information associated with themovement of products across different enterprises.

BACKGROUND OF THE INVENTION

FIG. 1 illustrates a supply chain 100. A set of manufacturers, 102_1 and102_2, distribute products to a set of warehouses 104_1 and 104_2,respectively. Warehouse 104_1 then distributes products to first andsecond distributors 106_1 and 106_2, while warehouse 104_2 distributesproducts to third and fourth distributors 106_3 and 106_4. The firstdistributor 106_1 then distributes products to one or more retailoutlets, such as a first retailer 108_1. The remaining distributorsdistribute products to retails 108_2, 108_3, and 108_4.

Arrows 110 illustrate the insertion of counterfeit goods into the supplychain 100. In one case, counterfeit goods are introduced at a warehouse104_2 and in another case counterfeit goods are introduced at adistributor 106_4. In either case, enterprises downstream from thecounterfeit insertion event have a difficult time identifying thecounterfeit goods.

Arrow 112 illustrates a possible path for an improper resale or returnof an item. In this case, the distributor 106_2 is bypassed andtherefore the resale and return rules potentially enforced by thedistributor 106_2 are bypassed.

Arrows 114 illustrate potential improper import paths into the supplychain 100. In this case, distributor 106_1 and retailer 108_1 directlyreceive improperly imported goods. Thus, import restrictions to beenforced by warehouses 104 are bypassed.

The foregoing supply chain abuses and many other supply chain abuses arecoming under increasing scrutiny. In addition, there is growing interestin tracking product movement to optimize legitimate supply chainoperations. For example, improved information on the movement of aproduct through a supply chain allows enterprises to more closelyanalyze trends in product consumption. This allows enterprises toimplement the supply chain more efficiently. In addition, morecomprehensive supply chain information allows more accurate predictionsof future consumption patterns.

The potential to thwart supply chain abuses and to improve supply chainefficiency has led various government agencies and large commercialenterprises to require the use of radio frequency (RG) tags. A radiofrequency tag is analogous to a bar code in the sense that it is used touniquely identify a product. However, where a bar code relies upon avisual pattern to uniquely identify a product, an RF tag uses an RFsignal signature to uniquely identify a product. An RF tag reader orscanner adjacent to an RF tag records the presence of the RF tag. Thereader or scanner can then deliver RF tag information to a database,allowing the RF tag information to be processed.

While the use of RF tags within a single enterprise (e.g., amanufacturer, a warehouse, a distributor, or a retailer) is known, thereare many challenges associated with the use of RF tags acrossenterprises (e.g., tracking RF tag information from a manufacturerthrough a retailer). One problem with cross-enterprise analysis isefficient processing of the vast amount of information associated withthe movement of multiple products through multiple tiers of multiplesupply chains.

In view of the foregoing, it would be highly desirable to provide atechnique for the efficient processing of cross-enterprise RF taginformation. Ideally, the processing of this information is used toimprove the function of the supply chain and to identify abuses withinthe supply chain.

SUMMARY OF THE INVENTION

The invention includes a computer readable medium with executableinstructions to analyze radio frequency (RF) tag information. Theexecutable instructions access cross-enterprise RF tag information,identify a product transition based upon the cross-enterprise RF taginformation, define a new product path based upon the producttransition, and apply logic to the new product path to facilitatecross-enterprise product flow analysis.

BRIEF DESCRIPTION OF THE FIGURES

The invention is more fully appreciated in connection with the followingdetailed description taken in conjunction with the accompanyingdrawings, in which:

FIG. 1 illustrates a prior art supply chain.

FIG. 2 illustrates the routing of RF tag information from a supply chainfor processing in accordance with an embodiment of the invention.

FIG. 3 illustrates a computer configured in accordance with anembodiment of the invention.

FIG. 4 illustrates processing operations associated with an embodimentof the invention.

FIG. 5 illustrates exemplary RF tag information that may be processed inaccordance with an embodiment of the invention.

FIG. 6 illustrates product paths corresponding to the data of FIG. 5.

Like reference numerals refer to corresponding parts throughout theseveral views of the drawings.

DETAILED DESCRIPTION OF THE INVENTION

FIG. 2 illustrates a supply chain 200 utilizing RF tag information.Manufacturers 102_1 through 102_N produce RF tag information uponmanufacturing products. For example, a manufacturer produces a product,places a tag on the product, and then uses an RF scanner to record aproduct number and attributes associated with the product (e.g., datemanufactured, location manufactured, type of product, and the like).This RF tag information is routed to a repository to form manufacturerRF tag data 202.

When the manufactured products are moved to warehouses, RF tag data areaccumulated. In particular, warehouses 104_1 through 104_N generatewarehouse tag data 204. In a similar manner, when the same products aremoved to distributors, more RF tag data are accumulated for theproducts. In particular, distributors 106_1 through 106_N generatedistributor tag data 206. Finally, when the products are moved to theretail level, more RF tag data are accumulated. FIG. 2 illustrates thatretailers 108_1 through 108_N produce retailer tag data 208.

A data analysis module 210, configured in accordance with an embodimentof the invention, processes the cross-enterprise RF tag data. The dataanalysis module 210 facilitates “horizontal” (i.e., across a row of thesupply chain, such as all manufacturers) data analyses as well as“vertical” (e.g., down a column of the supply chain, such as from amanufacturer to a retailer) data analyses.

FIG. 3 illustrates a computer 300 configured in accordance with anembodiment of the invention. The computer 300 includes standardcomponents including a central processing unit 302, which is connectedto a bus 304. Also connected to the bus 304 are input/output devices306. The input/output devices 306 may include a keyboard, mouse,monitor, printer, and the like. In addition, the input/output devices306 include network interfaces to communicate with a network ofcomputers generating RF tag data. So, for example, the input/outputdevices 306 are connected to one more data repositories storingmanufacturer tag data 202, warehouse tag data 204, distributor tag data206, and retailer tag data 208.

A memory 308 is also connected to the bus 304. The memory 308 stores RFtag information 310, such as RF tag information that is accessed throughthe input/output devices 306. A data analysis module 312 processes theRF tag information. The data analysis module includes executableinstructions to implement the RF tag processing functions describedherein.

FIG. 4 illustrates processing operations associated with one embodimentof a data analysis module of the invention. The first processingoperation of FIG. 4 is to access cross-enterprise RF tag information400. As used herein, the term cross-enterprise RF tag informationincludes “horizontal” cross-enterprise RF tag information (e.g., fromone warehouse to another) and “vertical” cross-enterprise RF taginformation (e.g., from a warehouse to a distributor to a retailer).

The cross-enterprise RF tag information is processed to identify aproduct transition 402. A product transition represents the movement ofa product across enterprises, either horizontally or vertically.

A new product path is then defined based upon a product transition 404.Logic is then applied to the new product path to facilitatecross-enterprise product flow analysis 406. The foregoing operations aremore fully appreciated in connection with some specific examples.

The invention can be used in connection with a variety of RF taginformation. For example, the RF tag information may relate to events,such as:

-   -   Commission tag    -   Sight tag    -   Pack tag into higher level assembly    -   Unpack    -   Ship    -   Receive    -   Product Return    -   Product Recall    -   Warrantee Claim    -   Medical Reimbursement Claim

The RF tag information may relate to sources, such as:

-   -   Map to location    -   Default Action    -   Authorized Operations

The RF tag information may also relate to locations, such as:

-   -   Company/Division/Region/Site/Area/SubArea    -   Transit bins    -   Business Function Performed        -   Manufacture        -   Distribution Level        -   Retail

The RF tag information can have historical components, such as:

-   -   Sequence of sightings    -   Sequence of Hierarchical Locations    -   Time periods spent at each location

In accordance with the invention, the movement of a tagged object can beviewed at many levels or within many dimensions. For example, thefollowing basic information may be available:

Jan. 1, 2004 10:00 Commission Big.Cinncinatti.plant3.room2→ Jan. 1, 200411:20 Pack Big.Cincinnatti.plant3.room4→ Jan. 3, 2004 07:30 SightNationWide.Colorado> Denver#2.receiving→ Jan. 4, 2004 14:03 ShipNationWide.Colorado> Denver#2.shipping→ Jan. 7, 2004 15:27 ReceiveGroceryExpress.Atlanta.dock3→ Jan. 8, 2004 08:53 SightGroceryExpress.Atlanda.storage. room27→ Jan. 8, 2004 13:11 ShipGroceryExpress. Atlanta.Shipping4→ Jan. 12, 2004 16:44 ReceiveEasyStop.Canada.Toronto. BackRoom→ Jan. 15, 2004 15:48 Sight EasyStop.Canada.Toronto. FrontRoom

This example can be used to illustrate various path dimensions that maybe exploited in accordance with the invention. The use of pathsfacilitates different analyses in accordance with the invention. The useof paths allows various amounts of data to be processed, either withfine resolution for detailed paths or course resolution for more generalpaths. Consider the following detailed paths defining the location ofthe tagged object in this example.

Big.Cinncinatti.plant3.room2

Big.Cincinnatti.plant3.room4

NationWide.Colarado.Denver#2.receiving

NationWide.Colarado.Denver#2.shipping

GroceryExpress.Atlanta.dock3

GroceryExpress.Atlanta.storage.room27

GroceryExpress.Atlanta.Shipping4

EasyStop.Canada.Toronto.BackRoom

EasyStop.Canada.Toronto.FrontRoom

Now consider a more generalized path that effectively filters or reducesthe amount of data. Instead of all locations, as in the previousexample, this example tracks corporate level locations.

Big

NationWide

GroceryExpress

EasyStop

For the same example, paths can be considered at a functional level:Manufacturer

Manufacturer

DistributorLevel

DistributorLevel1

DistributorLevel2

DistributorLevel2

Retail

Retail

The same example can be used to define paths at a national boundarylevel: USA

USA

USA

USA

USA

USA

USA

Canada

Canada

The same example can be used to define paths at an individual operationlevel: Commission

Pack

Sight

Sight

Receive

Sight

Ship

Receive

Sight

The same example can be used to define paths by absolute time:

Jan 1 2004 10:00

Jan 1 2004 11:20

Jan 3 2004 07:30

Jan 4 2004 14:03

Jan 7 2004 15:27

Jan 8 2004 08:53

Jan 8 2004 13:11

Jan 12 2004 16:44

Jan 15 2004 15:48

Paths can also be defined by the amount of time between transitions.Thus, in the foregoing example, the following path results: 0:0:00

0:1:20

1:06:27

3:01:25

0:17:26

0:04:42

4:03:33

3:23:04

The foregoing example can also be used to create a path for taglocations as categorized as transit times (time between sites): 1:06:27

3:01:25

4:03:33

As will be described in detail below, these various paths may becharacterized through regular expressions and/or other techniques. Pathexpression is used in accordance with the invention to limit the amountof data that needs to be processed, thereby facilitatingcross-enterprise analyses.

Various techniques may be used to form any given path. Consider the rawRF tag data of FIG. 5. Each row characterizes an RF tag event,specifying a tag reading source, the location for the tag readingsource, a business process (BP) code, a business function (BizFunction)associated with this level of the supply chain, a supply functionassociated with this level of the supply chain, transit characterizationfor the product at this point in the supply chain, and sitespecification. Observe that the business function, supply function, andtransit fields have different descriptive characterizations.

The following pseudo code may be used to create a path characterizingchanges in RF tag information.

PriorDesignation := null Path:= “ ” //initially an empty path While(remaining raw events) {     CurrentEvent := nextRawEvent    CurrentDesignation = Lookup Designation based on                    CurrentEvent, Level, and                     Tableof Levels     If (CurrentDesignation different from Prior Designation) {       Path = Path & “

” & CurrentDesignation        }     PriorDesignation := CurrentDesignation     }

The application of this pseudo code to the data of FIG. 5 results in thepath data of FIG. 6. Observe that the logic is initially applied to thebottom (row 13) of the raw data. Each row represents an event. The pathat each stage of processing is shown. Additions to the path occur atevent E1, E2, and E6.

In FIG. 6 there are 4 instances of a manufacturing

distribution path. These four instances have common product transitioncharacteristics. There are 3 instances of a manufacturing

distribution

retail path. These three instances have common product transitioncharacteristics. In a more complex example, individual retailers,distributors, and manufacturers can be specified. In such a case, commonproduct transition characteristics would be those that have commonspecific retailers, distributors, and manufacturers. Alternately, onecould define common product transition characteristics as havingspecific retailers and distributors, but any manufacturer. Any variationof such path definitions may be defined in accordance with theinvention.

Various forms of logic may be applied to paths created in accordancewith the invention. For example, path analysis can be used to determinemany important aspects of the state of a supply chain. A basic objectivein supply chain analysis is to gain visibility of all the goods ofinterest. When optimizing the quantity to manufacture, order, or ship itis desirable to know both the quantities at each location within thesupply chain and also their disposition. Are the products available forsale or are they being returned? Have the tagged cases shipped to aparticular retail store, been unpacked, stocked on the shelves, andpassed to the trash compactor (signifying the end-of-life for the case)?

In the simple example below, for a given time period and selection ofproducts, a total of 900 products have been issued into the distributionchain. Path analysis shows that 237 products have reached thedistributor and therefore should be available to be shipped to a retailestablishment. A total of 593 products have passed through a distributorto reach retail. A further 70 products have been reported as sold to aconsumer (through a point-of-sale tag reader, for example).

Path Quantity Manufacturer→Distributor 237Manufacturer→Distributor→Retailer 593Manufacturer→Distributor→Retailer→Consumer 70 900

By considering the rate of change of these categories over time, thevelocity (products per unit of time) is computed. This is a directmeasure of product flow. Flow at the consumer level is a direct measureof consumer demand. If the flow in the supply chain is unbalanced in thedirection of incoming supply exceeding demand, then inventory willaccumulate and eventually orders must stop. If demand exceeds supply,then eventually the supply chain is drained and the product will beout-of-stock.

In accordance with the invention, supply chain logic is used tocharacterize supply chain phenomenon, such as product velocity. Thissupply chain logic is in the form of executable instructions used toanalyze supply path transitions to facilitate the computation of supplychain metrics, such as product velocity.

Replenishment logic may also be applied to supply paths processed inaccordance with the invention. For many products, being out-of-stock atthe retail shelf level leads to loss of sales for that manufacturer aswell as for the specific product. In addition to the immediate problemof losing sales, consumers may find a substitute within the store—thiscan lead to a long-term loss of a customer for the out-of-stock brand.If the consumer does not find a satisfactory substitute the consumer mayleave without a purchase and possibly be a long-term lost customer forthe store. Hence, avoiding stock absence at the shelf level is a primaryobjective of both manufacturers and retailers. Consider the followingpaths identified in accordance with the invention.

Mfg

DistributionCenter

Mfg

DistributionCenter

Backroom

Mfg

DistributionCenter

Backroom

FrontRoom

This example illustrates possible paths for retail products to reach theshelf. Replenishment of the shelf may be triggered by executableinstructions that make calculations based on point-of-sale consumptioninformation and an estimated current inventory. Alternately,replenishment decisions may be made using executable instructions thattrack physical shelf inventory.

Using executable instructions to analyze the timing of the foregoingpaths, a manufacturer can detect that a product has not been replenishedfor over a preset period of time. The preset time may be based on pasthistory at a level that will avoid most false alarms, but provides aprompt indication of trouble. The preset time being exceeded canindicate that for some reason no shelf replenishment is taking place.Further analysis may determine that there is no backroom stock or thatthere is a procedural failure within the store. Thus, various tests maybe executed to avoid replenishment failure.

The invention is also successfully exploited in connection with tradepromotion. Trade promotion payments are a common method used bymanufacturers to pass incentives to retailers to promote and discountproducts to improve sales. Promotional agreements may be in the formthat the retailer agrees to sell an extra N units of the product if themanufacturer provides a promotional payment of $X per unit. In somecases, a retailer may accept the agreement, take delivery of the Nadditional units, and then sell all or part of the additional units toanother retailer at just below the normal wholesale price. This violatesthe trade promotion agreement and renders the retailer ineligible toreceive the payments. Consider the following example.

Mfg→DistributionCenter→StoreA Expected FlowMfg→DistributionCenter→StoreB Possible violation of promotionalagreement Mfg→DistributionCenter→StoreA→StoreB Violation of promotionalagreement

Path analysis can be used to determine if the retailer is in compliancewith trade promotion rules. The table above shows both the expected,normal flow for orders to this retailer, and several variants thatindicate a possible attempt to violate the agreement and fraudulentlyclaim trade promotion payments. Thus, in accordance with an embodimentof the invention, executable code is used to identify product flow pathsthat violate trade promotion criteria. For example, the trade promotioncriteria may be in the form of permissible trade path templates.Existing flow paths may then be compared to the permissible trade pathtemplates. In the event of a mismatch, a product flow exception isfired.

The invention is also successfully used in connection with taxationissues. Where taxation levels vary widely between regions, there is astrong incentive to pay taxes in low taxation states and then sell theafter tax products in high taxation states. This is particularlyprevalent with cigarettes in the US and many other parts of the world.In accordance with an embodiment of the invention, path analysis is usedto detect non-compliant movement of taxed goods. A simple example isshown below, where products intended for Nevada, and have tax paid inNevada, are diverted to California.

Mfg→NevadaDistribution→NevadaTaxPayments→ Compliant NevadaRetailMfg→NevadaDistribution→NevadaTaxPayments→ Non-Compliant CaliforniaRetail

Thus, in accordance with an embodiment of the invention, a complianttaxation path template is created and is tested against various existingproduct paths to identify potentially non-compliant situations.

In addition to taxation compliance, the invention is successfully usedin connection with regulatory compliance. There are numerous regulationson the movement of certain kinds of products. For example, it iscurrently illegal to re-import pharmaceuticals from other countries.Below is an example of a compliant trade and a non-compliant trade.

USA→Canada→Retail Sale Compliant USA→Canada→USA→Retail SaleNon-Compliant

Thus, in accordance with the invention, once paths are defined, they maybe tested for boundary transitions (e.g., Canada to USA) that do notcomply with regulatory requirements. In particular, executableinstructions associated with the data analysis module 312 may be used toidentify non-compliant activity of this type.

It is also against FDA regulations for pharmaceuticals to be sold to a“closed-door pharmacy” and then be redistributed. Below is an example ofcompliant and non-compliant activity of this type.

Mfg→Distributor→Closed-Door Pharmacy CompliantMfg→Distributor→Closed-Door Pharmacy→Distributor Non-Compliant

Executable instructions may be used to identify redistribution from aclosed-door pharmacy, in accordance with an embodiment of the invention.

The invention is also successfully used in accordance with recallinitiatives. Products in the market place may be recalled for manyreasons. Shipments of meat may be contaminated, pharmaceuticals may havea bad batch, cigarettes may be contaminated by poor production controlduring manufacture or even have there taste altered by proximity toother products, like detergent.

The path analysis techniques of the invention can aid recall initiativesin a number of ways. In one embodiment of the invention, basic steps inthe recall process include:

-   -   1. Identify that a certain set of goods must be recalled and        note the serialized identification of these products.    -   2. Issue a “Recall” operation on all of the affected products.    -   3. Analyze the paths of the affected products to identify their        current locations    -   4. Notify representatives at the current locations    -   5. Where recalled products are found, the operation “Return to        Manufacturer” should be performed.

Once the above operations are taken, the continued operation of therecall may be monitored via path analysis. The primary objective is toensure that the products are removed from the supply chain. Anadditional objective is to ensure that the products are physicallyreturned to the manufacturer (or otherwise disposed of). It is alsoimportant to correctly credit those who return recalled products. Beloware various examples of how path analysis associated with the inventioncan be used in connection with recall initiatives.

Commission→Ship→Receive→Recall→Return→Receive at Credit MfgCommission→Ship→Receive→Recall→RetailSale Alert - No CreditCommission→Ship→Receive→Recall→Return→ Alert - No RetailSale Credit

The invention is also successfully used in connection with solvingproblems associated with cross-contamination. Cross-contamination occurswhen one batch of products adversely impacts an adjacently positionedbatch of products. Cross-contamination also occurs as a result of aspecific event, such as spilling of a cleanser, which impacts allsusceptible products within the region of the spill. The contaminationmay not be discovered until later, for example, when a smoker complainsthat the cigarette smells “funny”.

In one embodiment of the invention, the basic steps to resolve across-contamination problem include:

-   -   1. Exemplar product is reported and confirmed.    -   2. Use path analysis on this exemplar product to find its        complete history.    -   3. Track back through that history to find where the        contamination occurred.    -   4. Identify the approximate time period of the contamination.    -   5. Use path analysis both at the location level and intersect        this with time information to identify all other products which        were in the same place at the same time as the contamination.    -   6. Issue a recall on all the potentially contaminated products.

These operations maybe implemented as a set of executable instructionsassociated with the data analysis module 312.

The invention is also successfully used to solve product obsolescenceproblems. Product obsolescence can be a health regulation complianceissue to avoid selling products that have exceeded their shelf life.Product obsolescence is also a commercial issue because most retailerswill not accept, or pay for, products that do not have a sufficientremaining shelf life when received. A retailer may return some productsfor credit if the optimal sales date is passed, for example oldmagazines and food products that have aged on the shelf. Productobsolescence also applies to seasonal products, like gift-wrapping andfor electronic products that are superseded by a newer model.

Path analysis may be extended to allocate “pseudo” steps or events in aproduct path by flagging events based on the approach to the expirationof a predetermined shelf life.

Fresh→ OK to ship Fresh→20 Days Ship these first to avoid loss Fresh→10Days Will not be accepted by retailer Fresh→5 Days Mark down in storeFresh→0 Days Recall

For example, at the time of manufacturing or packaging a good, a“lifetime” value is associated with the good. Executable instructionsare used to compare the lifetime value against a current date to computethe number of days remaining in the life of the product. The number ofdays is compared to a set of rules, for example of the type shown above,to identify actions that may or may not be taken in connection with theproduct.

The invention may also be used in connection with identifying unusual orproblematic flow in the supply chain. That is, path analysis can be usedboth to look for product movement behavior that is expected and also todetect unusual behavior. Consider the following example:

Mfg_Out→LowSpeed→HighSpeed→BackRoom→ Normal FrontRoomMfg_Out→LowSpeed→HighSpeed→LowSpeed→ RecirculationHighSpeed→BackRoom→FrontRoom on conveyor

This real world example shows two different paths through the sameretail distribution center using an automated conveyor system. The firstentry is a normal path showing the products taking one trip on the lowspeed and high speed conveyors. The second path shows that the productstook additional trips on the conveyors. Investigation showed that thiswas because the conveyor system would recirculate products if it did notsuccessfully read the bar codes on the cases. A similar analysis mayshow recirculation in the supply chain where products go through thesame distribution center multiple times. This may indicate an attempt todefraud on trade promotion payments. Thus, a flow pattern that isinconsistent with expected flow patterns, may trigger an exception, evenif it is unknown what the problem is or the nature of the exception.

The invention is also successfully used in connection with theidentification of counterfeit goods. Counterfeit detection is animportant problem for pharmaceuticals in the USA and worldwide. Otherproducts, such as cigarettes and fashion items, are also susceptible tocounterfeiting.

Various path analyses in accordance with the invention may be used todetect counterfeit goods. For example, consider a situation in which amanufacturer of a legitimate product uses a commission tag. In thiscase, all products without a tag are suspect.

Commission→Ship→Receive→RetailSale Compliant product Receive→RetailSaleNot Compliant - Counterfeit

In this example, executable instructions are used to identify theabsence of a commission event in a path.

The techniques of the invention may also be used to identifyunauthorized product importation. All instrumented product movementsestablish a path for a product. These paths can be analyzed to detectunauthorized movements. For example:

USA→Canada→Retail Authorized USA→Canada→USA→Retail Not Authorized

Again, executable instructions are used to identify impermissibleboarder transitions.

Those skilled in the art will appreciate that various techniques may beused to implement the path analyses of the invention. Regularexpressions are one exemplary way to match specific path expressions todiscover targeted behavior. Other approaches include using graphicalmanipulation to build descriptions of paths that can be matched by asimple equality.

Regular expressions are a well-established mathematical way ofexpressing a grammar that may be used to recognize a sequence of tokens.It has been demonstrated that a finite state machine, for example anyreal world computer, can recognize anything expressible as a regularexpression. This means that in a rather fundamental sense, regularexpressions are the most powerful practical way to express patterns ofstates. Regular expressions are mathematically equivalent to statesequence diagrams of arbitrary finite complexity.

Regular expressions are very powerful but also may be complex toevaluate. There are variations in regular expression syntax. By way ofexample, the Java regular expression package may be used. An exemplarysubset of the syntax is shown below.

X? X, once or not at all

X* X, zero or more times

X+ X, one or more times

X{n} X, exactly n times

X{n,} X, at least n times

X{n, m} X, at least n but not more than m times

Logical operators

XY X followed by Y

X|Y Either X or Y

(X) X, as a capturing group

Predefined Character Classes

Any character

Character classes

[abc] a, b, or c (simple class)

[^abc] Any character except a, b, or c (negation)

Relying upon this syntax, various rules can be concisely expressed. Forexample, suppose that it is desirable to express that distributionwithin the USA, and also from the USA to Canada, is acceptable. In thiscase, the following regular expression may be used.

USA+

(USA|Canada+)

This pattern would accept distribution within the US

USA

USA

USA

USA

And also from the US into Canada

USA

USA

USA

USA

USA

USA

USA

Canada

Canada

But, it would reject re-importation into the US USA

USA

USA

USA

USA

USA

USA

Canada

Canada

USA

This example demonstrates how a simple single expression or rule can beused to test a variety of product paths, in accordance with theinvention.

A regular expression can also be formed to define non-compliantdistribution. The following expression precludes re-importation into theUS.

USA+

[

USA]+

USA+

This expression will match any product path that starts in the US,leaves the US (^USA) and then returns to the US.

A regular expression may also be used to characterize the normal lifecycle of a product. Consider the following exemplary life cycle:

Commission

Sight*

Pack{1}

Sight*

Unpack{1}

Sight*

Similarly, non-compliant life cycle events may also be defined, such as:

.*

Commission

.*

Commission

.*

The above expression will match any sequence that includes two or morecommission operations on a tag. Similarly, it would be non-compliant fora tagged object to be packed twice, without an intervening unpack.

.*

pack{1}

[unpack]*

pack

.*

Consider the diversion or re-circulation of a product that is not incompliance with marketing agreements. The following regular expressionmay be used in this situation.

Manufacturer+

DistributorLevel1+

DistributorLevel2+

Retail+

The regular expression above may be a compliant path for a specificindustry. The regular expression below will match any re-circulationfrom level 2 back to level 1.

.*

DistributorLevel2+

.*

+DistributorLevel1+

The following regular expression will match any re-circulation from theretail level backwards through the supply chain.

.*

Retail+

.*

DistributorLevel1|DistributerLevel2|Manufacturer

.*

A variety of regular expressions may be used to identify counterfeitactivity. For example, any tag history that does not begin with acommission event from an authorized source can indicate a fraudulent tagintroduced into the supply chain. The following regular expressionidentifies a product path that does not include the appropriatecommission tag.

ACommission

.*

The following regular expression detects a situation where acounterfeiter copies the tag of a product distributed in Western US andthen introduces the product in another region.

.*

WesternRegionDistribution

.*

WesternRegionDistribution

Regular expressions may also be used for period based event detection.Consider the following transit times:

-   -   1:06:27        3:01:25        4:03:33

This information is difficult to match against a simple regularexpression. The information can be recast in an approximated form bysimply representing each day as say, D.

-   -   D        DDD        DDDD

One could then look for any transit times that were suspiciously long:

-   -   .*        D{5,}        .*        The foregoing expression matches any transit time of 5 days or        longer.

Those skilled in the art will appreciate that the paths formed inaccordance with the invention may be analyzed using any number oftechniques, including analysis of product transition events, testing ofproduct sources, tracking of product locations, analysis of producthistory, and scrutiny of product statistics. Other product path eventsthat may be analyzed include product transition boundary information,product absolute resident time information, and product transitinformation.

An embodiment of the present invention relates to a computer storageproduct with a computer-readable medium having computer code thereon forperforming various computer-implemented operations. The media andcomputer code may be those specially designed and constructed for thepurposes of the present invention, or they may be of the kind well knownand available to those having skill in the computer software arts.Examples of computer-readable media include, but are not limited to:magnetic media such as hard disks, floppy disks, and magnetic tape;optical media such as CD-ROMs and holographic devices; magneto-opticalmedia such as floptical disks; and hardware devices that are speciallyconfigured to store and execute program code, such asapplication-specific integrated circuits (“ASICs”), programmable logicdevices (“PLDs”) and ROM and RAM devices. Examples of computer codeinclude machine code, such as produced by a compiler, and filescontaining higher-level code that are executed by a computer using aninterpreter. For example, an embodiment of the invention may beimplemented using Java, C++, or other object-oriented programminglanguage and development tools. Another embodiment of the invention maybe implemented in hardwired circuitry in place of, or in combinationwith, machine-executable software instructions.

The foregoing description, for purposes of explanation, used specificnomenclature to provide a thorough understanding of the invention.However, it will be apparent to one skilled in the art that specificdetails are not required in order to practice the invention. Thus, theforegoing descriptions of specific embodiments of the invention arepresented for purposes of illustration and description. They are notintended to be exhaustive or to limit the invention to the precise formsdisclosed; obviously, many modifications and variations are possible inview of the above teachings. The embodiments were chosen and describedin order to best explain the principles of the invention and itspractical applications, they thereby enable others skilled in the art tobest utilize the invention and various embodiments with variousmodifications as are suited to the particular use contemplated. It isintended that the following claims and their equivalents define thescope of the invention.

The invention claimed is:
 1. A computer-readable medium storinginstructions that, in response to execution, cause a system to performoperations, comprising: identifying one or more transitions of a productbetween two different enterprise types based on an analysis ofcross-enterprise radio frequency tag information; defining generatingproduct path information based on the one or more transitions; anddetermining one or more trends in product flow and product consumptionbased on another analysis of the product path information.
 2. Thecomputer-readable medium of claim 1, wherein the generating the productpath information comprises classifying the product path information intoa group according to a common product transition characteristic.
 3. Thecomputer-readable medium of claim 1, wherein the generating the productpath information comprises characterizing a state sequence of theproduct path information.
 4. The computer-readable medium of claim 1,wherein the operations further comprise identifying a product flowexception based on a comparison between the product path information andone or more permissible trade path templates.
 5. The computer-readablemedium of claim 1, wherein the operations further comprise applyingpattern matching between the product path information and a testtemplate.
 6. The computer-readable medium of claim 1, wherein theoperations further comprise applying defined supply chain logic to theproduct path information.
 7. The computer-readable medium of claim 1,wherein the operations further comprise applying defined replenishmentprocess failure logic to the product path information.
 8. Thecomputer-readable medium of claim 1, wherein the operations furthercomprise applying defined trade promotion logic to the product pathinformation.
 9. The computer-readable medium of claim 1, wherein thelogic includes operations further comprise applying defined taxationlogic to the product path information.
 10. The computer-readable mediumof claim 1, wherein the operations further comprise applying definedregulatory compliance logic to the product path information.
 11. Thecomputer-readable medium of claim 1, wherein the operations furthercomprise applying defined recall logic to the product path information.12. The computer-readable medium of claim 1, wherein the operationsfurther comprise applying defined obsolescence logic to the product pathinformation.
 13. The computer-readable medium of claim 1, wherein theoperations further comprise applying defined cross-contamination logicto the product path information.
 14. The computer-readable medium ofclaim 1, wherein the operations further comprise applying definedunusual flow logic to the product path information.
 15. Thecomputer-readable medium of claim 1, wherein the operations furthercomprise applying defined inventory shrinkage logic to the product pathinformation.
 16. The computer-readable medium of claim 1, wherein theoperations further comprise applying defined counterfeit identificationlogic to the product path information.
 17. The computer-readable mediumof claim 1, wherein the operations further comprise applying definedunauthorized importation logic to the product path information.
 18. Thecomputer-readable medium of claim 1, wherein the operations furthercomprise analyzing at least one of a product transition event, a productsource, a product location, a product history, or a product statistic.19. The computer-readable medium of claim 1, wherein the operationsfurther comprise analyzing at least one of product transition boundaryinformation, product absolute resident time information, or producttransit information.
 20. The computer-readable medium of claim 1,wherein the operations further comprise applying a regular expression tothe product path information.
 21. The computer-readable medium of claim2, wherein the classifying further comprises classifying the productpath information into the group based on a classification of at leastone of the two enterprises as a manufacturer, a warehouse, adistributor, or a retailer.
 22. The computer-readable medium of claim 1,wherein the operations further comprise filtering the product pathinformation yielding filtered product path information that representsrespective locations as one of a manufacturer, a warehouse, adistributer, or a retailer, wherein the identifying the trend comprisesidentifying the trend based on analysis of the filtered product pathinformation.
 23. The computer-readable medium of claim 1, wherein thecross-enterprise radio frequency tag information respectively classifiesthe two enterprises as one of a manufacturer, a warehouse, adistributor, or a retailer.
 24. The computer-readable medium of claim 1,wherein the generating the product path information comprises generatingthe product path information to characterize the cross enterprise radiofrequency tag information in terms of the one or more transitionsbetween the two different enterprise types.
 25. A method, comprising:determining, by a system comprising a processing device, producttransitions between two different enterprise types comprising analyzingcross-enterprise radio frequency tag information; generating productpath information based on the product transitions; and identifying atleast a first trend in product flow and a second trend in productconsumption comprising analyzing the product path information.
 26. Themethod of claim 25, wherein the generating comprises generating theproduct path information to characterize the cross-enterprise radiofrequency tag information in terms of the product transitions betweenthe two enterprise types.
 27. The method of claim 26, wherein theenterprise types comprise at least two from a group of enterprise typescomprising manufacturer, warehouse, distributor, and retailer.
 28. Asystem, comprising: means for identifying one or more transitions of aproduct between two different enterprise types based on an analysis ofcross-enterprise radio frequency tag information; means for generatingproduct path information based on the one or more transitions; and meansfor identifying one or more trends in product flow and productconsumption based on another analysis of the product path information.29. The system of claim 28, wherein the means for generating comprisesmeans for characterizing the cross-enterprise radio frequency taginformation in terms of the one or more transitions between the twodifferent enterprise types.
 30. A system, comprising: a processor,communicatively coupled to a memory, that executions or facilitatesexecution of computer-executable instructions stored by the memory to atleast: determine product transitions between two different enterprisetypes using an analysis of cross-enterprise radio frequency taginformation; generate product path information based on the producttransitions; and identify a trend in product flow and productconsumption using another analysis of the product path information. 31.The system of claim 30, wherein the processor further executes orfacilitates execution of the computer-executable instructions togenerate the product path information to describe the cross-enterpriseradio frequency tag information in terms of transitions between the twodifferent enterprise types.